academic-rebuttal

Draft evidence-backed rebuttals correcting false impressions in venue reviews.

4|2|Updated Feb 19, 2026
One-click install
npx skills add https://github.com/drunkcoding/AgentSkillsArxiv --skill academic-rebuttal
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: academic-rebuttal
Source: https://github.com/drunkcoding/AgentSkillsArxiv/tree/main/skills/academic-rebuttal
Command: npx skills add https://github.com/drunkcoding/AgentSkillsArxiv --skill academic-rebuttal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Drafts professional, evidence-based author responses that counter reviewer false impressions while preserving tone and credibility.

Core Features & Use Cases

  • False impression taxonomy and resolution playbooks for eight FI types
  • Stage-wise rebuttal workflow: triage, drafting, compression, and policy checks
  • Ready-to-use phrase templates and structured response patterns for major venues
  • Cross-venue guidance (OpenReview/HotCRP) and platform mechanics references

Quick Start

Provide a concise, evidence-backed rebuttal that directly addresses the top concern with explicit revision commitments.

Frequently Asked Questions about academic-rebuttal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a conference rebuttal that corrects reviewer factual errors?

A conference rebuttal corrects reviewer false impressions by providing evidence-backed responses and explicit revision commitments. You identify factual errors in reviews and counter them with structured, professional arguments that preserve credibility.

How do I format an author response for OpenReview or HotCRP within word limits?

Formatting an author response for OpenReview or HotCRP requires applying venue-specific templates and policy-aware structures. You compress evidence-backed arguments into concise statements that satisfy platform word limits and explicit revision commitment requirements.

What is the best way to handle false impressions in reviewer feedback for ML conferences?

Handling false impressions in reviewer feedback for ML conferences involves classifying the error type and applying a targeted resolution playbook. You draft evidence-based responses that directly counter factual misunderstandings while adhering to venue policies.

Does this rebuttal workflow support both computer systems venues and ML conferences?

Yes, the rebuttal workflow supports computer systems venues like OSDI, SIGCOMM, and SOSP, alongside ML conferences such as NeurIPS, ICML, and ICLR. It provides cross-venue guidance and platform-specific templates for both OpenReview and HotCRP.

What are the steps to draft a rebuttal for a major computer systems conference?

Drafting a rebuttal involves a stage-wise workflow: triage reviews to identify false impressions, draft evidence-backed responses, compress text to meet word limits, and perform policy checks. This ensures structured, compliant author responses.